Pages that link to "Item:Q1092542"

The following pages link to Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions (Q1092542):

Displaying 50 items.

• Informational complexity criteria for regression models. (Q1274149) (← links)
• Bootstrapping log likelihood and EIC, an extension of AIC (Q1293718) (← links)
• Semiparametric estimation of count regression models (Q1305681) (← links)
• Optimal product positioning based on paired comparison data (Q1305801) (← links)
• A latent structure double hurdle regression model for exploring heterogeneity in consumer search patterns. (Q1305807) (← links)
• A maximum likelihood method for latent class regression involving a censored dependent variable (Q1309410) (← links)
• Estimating latent distributions in recurrent choice data (Q1309419) (← links)
• A latent class procedure for the structural analysis of two-way compositional data (Q1314823) (← links)
• An application of multiple comparison techniques to model selection (Q1388158) (← links)
• Model selection using AIC in the presence of one-sided information (Q1399268) (← links)
• Factor models for multivariate count data. (Q1426353) (← links)
• Modified AIC rule for model selection in combination with prior estimated noise models (Q1614314) (← links)
• Robust growth mixture models with non-ignorable missingness: models, estimation, selection, and application (Q1621300) (← links)
• Information content in data sets: a review of methods for interrogation and model comparison (Q1637473) (← links)
• Penalised inference for lagged dependent regression in the presence of autocorrelated residuals (Q1640650) (← links)
• Model selection criteria based on cross-validatory concordance statistics (Q1642996) (← links)
• Extending AIC to best subset regression (Q1643010) (← links)
• Slice-Gibbs sampling algorithm for estimating the parameters of a multilevel item response model (Q1645032) (← links)
• Bootstrap order determination for ARMA models: a comparison between different model selection criteria (Q1658076) (← links)
• Mixture-based clustering for the ordered stereotype model (Q1660188) (← links)
• Latent profile analysis with nonnormal mixtures: a Monte Carlo examination of model selection using fit indices (Q1660200) (← links)
• Automatic emergence detection in complex systems (Q1674830) (← links)
• A theoretical note on the prior information criterion (Q1680995) (← links)
• Local influence for spatially correlated binomial data: an application to the \textit{spodoptera frugiperda} infestation in corn (Q1695267) (← links)
• Asymptotics of AIC, BIC, and RMSEA for model selection in structural equation modeling (Q1695635) (← links)
• Investigating dependence between frequency and severity via simple generalized linear models (Q1726156) (← links)
• On the method of approximate Fisher scoring for finite mixtures of multinomials (Q1731201) (← links)
• An introduction to the Bayes information criterion: theoretical foundations and interpretation (Q1733295) (← links)
• Linear algorithms for radioelectric spectrum forecast (Q1736867) (← links)
• An information criterion for model selection with missing data via complete-data divergence (Q1744714) (← links)
• The exponentiated Gumbel type-2 distribution: properties and application (Q1751472) (← links)
• Mixture of D-vine copulas for modeling dependence (Q1800071) (← links)
• On the use of information criteria in analytic hierarchy process (Q1848617) (← links)
• AIC, overfitting principles, and the boundedness of moments of inverse matrices for vector autotregressions and related models. (Q1861397) (← links)
• CATSCALE: A stochastic multidimensional scaling methodology for the spatial analysis of sorting data and the study of stimulus categorization (Q1896215) (← links)
• Deriving ultrametric tree structures from proximity data confounded by differential stimulus familiarity (Q1901365) (← links)
• A parametric procedure for ultrametric tree estimation from conditional rank order proximity data (Q1901372) (← links)
• A mixture likelihood approach for generalized linear models (Q1901393) (← links)
• Forecasting using predictive likelihood model averaging (Q1929119) (← links)
• Global convergence of the EM algorithm for unconstrained latent variable models with categorical indicators (Q1940987) (← links)
• Self-concordant analysis for logistic regression (Q1952060) (← links)
• Akaike's information criterion and recent developments in information complexity (Q1977905) (← links)
• Statistical tests for comparing possibly misspecified and nonnested models (Q1977909) (← links)
• Key concepts in model selection: Performance and generalizability (Q1977913) (← links)
• Sequential truncation of \(R\)-vine copula mixture model for high-dimensional datasets (Q1980359) (← links)
• On the usefulness of the logarithmic skew normal distribution for describing claims size data (Q2004090) (← links)
• A Lasso-penalized BIC for mixture model selection (Q2009036) (← links)
• A comparison of some criteria for states selection in the latent Markov model for longitudinal data (Q2009042) (← links)
• Covariance components selection in high-dimensional growth curve model with random coefficients (Q2018598) (← links)
• Strong consistency of log-likelihood-based information criterion in high-dimensional canonical correlation analysis (Q2023829) (← links)